A ligand-based approach for the in silico discovery of multi-target inhibitors for proteins associated with HIV infection

Many questions have been posed about acquired immunodeficiency syndrome (AIDS) pathogenesis. Is human immunodeficiency virus (HIV) both necessary and sufficient to cause AIDS? Is AIDS essentially an autoimmune disease, triggering apoptosis, or is virus infection the cause of T helper lymphocyte depletion? What is the significance of HIV tropism and the role of macrophages and dendritic cells in AIDS? Is there viral latency and why is there usually a long period between infection and AIDS? Is HIV variation a crucial aspect of its pathogenesis and, if so, do virulent strains emerge? Although this article provides few definitive answers, it aims to focus commentary on salient points. Overall, it is increasingly evident that both the tropism and burden of HIV infection correlate closely with the manifestations of disease. Show more

The receiver operator characteristic (ROC) curves are commonly used in biomedical applications to judge the performance of a discriminant across varying decision thresholds. The estimated ROC curve depends on the true positive rate (TPR) and false positive rate (FPR), with the key metric being the area under the curve (AUC). With small samples these rates need to be estimated from the training data, so a natural question arises: How well do the estimates of the AUC, TPR and FPR compare with the true metrics? Through a simulation study using data models and analysis of real microarray data, we show that (i) for small samples the root mean square differences of the estimated and true metrics are considerable; (ii) even for large samples, there is only weak correlation between the true and estimated metrics; and (iii) generally, there is weak regression of the true metric on the estimated metric. For classification rules, we consider linear discriminant analysis, linear support vector machine (SVM) and radial basis function SVM. For error estimation, we consider resubstitution, three kinds of cross-validation and bootstrap. Using resampling, we show the unreliability of some published ROC results. Companion web site at http://compbio.tgen.org/paper_supp/ROC/roc.html edward@mail.ece.tamu.edu. Show more